Studies Of Social Network Structure And The Influence Of Its Users

Social network is a new type of network applications in recent years. With the continuous development of Internet technology, more and more people are no longer confined to communicate through telephone, SMS and other traditional ways. They try to communicate on the Internet, which makes the social network begin to rise, and gradually become one of the main platforms of information distribution and transmission. As the leader in social network, Sina weibo is becoming a hot spot of social network research. For this reason, this thesis uses social network analysis method and user influence algorithm, studies network features and the influence of a single user of two types of sina weibo user network.Firstly, the thesis elaborates related research background and significance are elaborated. Then related researches are reviewed in three aspects:social network, social network analysis method and user influence. Lastly main contents of this paper are presented. Secondly, several concepts and theories which will be utilized in the next chapters are introduced. On this basis, on one hand, first of all, the reason why choose sina weibo as the research object is addressed. Then we discuss the method of data acquisition, and use the social network analysis method to calculate and analysis several network characteristic parameters of two types of user network. Common expression is that the interaction between users is not frequently enough, and communication is relatively scarce, and two types of network have a leader character. Then difference displays in:firstly, the cross coupling will appear between the V users, and the coupling relationship between the network is integrity. However, ordinary users only interact with the user exists in the field of the same concern, forming obvious zoning; Secondly, the access to information of ordinary users is limited, and the leader role in network is far lower than V star users. On the other hand, using the user influence algorithm to calculate and analysis the individual user’s influence in the above two types of user network. Firstly, in this chapter, we combine the characteristics of sina weibo to select reasonable evaluation index, then through the selection of indicators to improve PageRank algorithm, and build the sina weibo user influence algorithm (UIRank algorithm), finally we use UIRank algorithm to analyze user’s influence. The calculation result shows that, UIRank algorithm is better than the existing celebrity list of sina weibo as well as the original PageRank algorithm. The empirical analysis also found that V star user as a public figure, they have many fans and strong power, so their influence is significantly greater than the average user. V star have to be cautious with the their own influence, pay attention to the effects on the public of their behavior. In addition, Sina weibo operators can choose V users as the source of releasing information, if they want to release or transfer the important message.